CAJ | 학술논문

针对云计算环境下满足负载均衡、自动伸缩、绿色节能等需求时所面临的虚拟机(VM)迁移问题,该文设计一种面向云计算基础设施基于工作负载预测的整合调度算法.通过有机结合基于工作负载预测的主动控制技术和基于实际系统状态信息的被动控制技术,并采用指数平滑预测模型预测未来时刻的工作负载情况,提出虚拟机选择阶段最大未来工作负载优先和虚拟机安置阶段比较资源需求队列的虚拟机整合算法.仿真表明,该算法利用基于预测的资源整合方式减少了服务器使用量、虚拟机迁移次数和服务等级协议违例次数,有效提升了以数据中心为核心的云基础设施整体资源利用率.
침대운계산배경하만족부재균형、자동신축、록색절능등수구시소면림적허의궤(VM)천이문제,해문설계일충면향운계산기출설시기우공작부재예측적정합조도산법.통과유궤결합기우공작부재예측적주동공제기술화기우실제계통상태신식적피동공제기술,병채용지수평활예측모형예측미래시각적공작부재정황,제출허의궤선택계단최대미래공작부재우선화허의궤안치계단비교자원수구대렬적허의궤정합산법.방진표명,해산법이용기우예측적자원정합방식감소료복무기사용량、허의궤천이차수화복무등급협의위례차수,유효제승료이수거중심위핵심적운기출설시정체자원이용솔.
For issue of Virtual Machine (VM) migration in cloud computing environment when it comes to meeting the demands of load balancing, auto scaling, green energy-saving, etc. This paper design a scheduling algorithm that is cloud computing infrastructures oriented and workload prediction based. By organically integrating the active control technology based on workload prediction and the passive control technology based on status information of actual system, as well as with the exponential smoothing prediction model to predict the workload condition in future time, a VM consolidation algorithm is put forward which takes the maximum future workload as first in the VM selection stage and compares the resource demand queues in the VM placement stage. The simulation results show that the algorithm uses the prediction-based resource integration to reduce the number of servers and virtual machine migrations as well as service level agreement violations, effectively increasing the overall resource utilization of data center as the core of the cloud infrastructure.